如何在我的图中绘制滚动相关系数？

Question

这是我的代码。通过谷歌，我刚刚找到了一个提示，但它并没有真正起作用，可能是因为两种资产类别之间的滚动（50）相关性。我想在右上角有一个传说中的相关系数。

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime as dt, timedelta as td
from pandas_datareader import data as  pdr
import numpy as np


#'--------------------------------------
#ZUSATZ: automatic request of online data
#--------------------------------------

startyear =2020
startmonth =1
startday = 1

datestring = dt.strftime(dt.now(), "%d/%m/%Y")

start = dt(startyear,startmonth,startday) #Set starting time for datesample
now = dt.now()

asset1 = input("Enter the stock symbol (enter 'quit' to stop):").upper()
asset2 = input("Enter the stock symbol (enter 'quit' to stop):").upper()


a1 = pdr.get_data_yahoo(asset1,start,now).reset_index()
a2 =pdr.get_data_yahoo(asset2,start,now).reset_index()

a1= pd.DataFrame(a1[["Date","Adj Close"]])
a1.columns =["Date " + asset1, "Adj Close " + asset1]

a2= pd.DataFrame(a2[["Date", "Adj Close"]])
a2.columns =["Date " + asset2, "Adj Close " + asset2]

asset = pd.concat([a1,a2], axis=1)

points_to_plot = 300
fig = plt.figure()
fig.suptitle("Correlation " + datestring)
ax1 = fig.add_subplot(1,1,1)
ax1.set_ylabel('Correaltion', fontsize = 12)
ax1.set_xlabel('Day', fontsize = 12)
label1 = ax1.set_xticklabels(ax1.get_xticklabels(), rotation = 90,fontsize=5,alpha=0.5)
ax1.set_title(f"{asset1} & {asset2}, last {points_to_plot} days", fontsize=14)

correlation_line = asset["Adj Close " +asset1].rolling(50).corr(asset["Adj Close " + asset2])[-300:].plot()
plt.legend((correlation_line, 'line-regression r={}'), 'best')

plt.show()

Answer 1

以防万一有人感兴趣。我是这样解决的。

当然，如果有人可以告诉我“老兄，你需要太多代码”，我愿意学习，谢谢。我也很感兴趣是否可以在热图中的折线图上标记 0.79 的相关性。

如果有人有想法？

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from datetime import datetime as dt, timedelta as td
from pandas_datareader import data as  pdr
import numpy as np
import scipy as sc


#'--------------------------------------
#ZUSATZ: automatic request of online data
#--------------------------------------


startyear =2020
startmonth =1
startday = 1

datestring = dt.strftime(dt.now(), "%d/%m/%Y")

start = dt(startyear,startmonth,startday) #Set starting time for datesample
now = dt.now()

asset1 = input("Enter the stock symbol (enter 'quit' to stop):").upper()
asset2 = input("Enter the stock symbol (enter 'quit' to stop):").upper()

points_to_plot = 300

fig = plt.figure()
fig.suptitle("Correlation " + datestring)
ax1 = fig.add_subplot(1,2,1)
ax2 = fig.add_subplot(1,2,2)
ax2.set_ylabel("Correaltion",fontsize = 12)
ax2.set_xlabel("Days", fontsize = 12)
label1 = ax1.set_xticklabels(ax1.get_xticklabels(), rotation = 90,fontsize=5,alpha=0.5)
ax2.set_title(f"{asset1} & {asset2}, last {points_to_plot} days", fontsize=14)
ax1.set_title(f"{asset1} & {asset2}, last {points_to_plot} days", fontsize=14)

a1 = pdr.get_data_yahoo(asset1,start,now).reset_index()
a2 =pdr.get_data_yahoo(asset2,start,now).reset_index()

a1= pd.DataFrame(a1[["Date","Adj Close"]])
a1.columns =["Date " + asset1, "Adj Close " + asset1]

a2= pd.DataFrame(a2[["Date", "Adj Close"]])
a2.columns =["Date " + asset2, "Adj Close " + asset2]

asset = pd.concat([a1,a2], axis=1)

correlation_line = asset["Adj Close " + asset1].rolling(50).corr(asset["Adj Close " + asset2])[-300:].plot()



df= pd.DataFrame(asset, columns=["Adj Close "+ asset1, "Adj Close " + asset2])
print(df)
corrMatrix = df.corr()
print(corrMatrix)

sns.heatmap(corrMatrix, annot=True, ax=ax1)


plt.show()